Matrix variate extended skew normal distributions
-
Wei Ning
and
Arjun K. Gupta
Abstract.
It was Azzalini (1985) who introduced the univariate skew
normal distribution family with a shape parameter 
, and
then extended skew normal distribution family by adding an
additional shape parameters 
. Azzalini and Dalla Valle (1996)
extended the results to the multivariate case. Basic properties for the
univariate and multivariate cases were summarized by Azzalini
(2005). Chen and Gupta (2005) considered the matrix variate skew
normal distribution family and proposed the moment generating
function and demonstrated that the distribution of the quadratic form of the skew normal matrix variate
follows a Wishart distribution. Their results were generalized by Harrar and Gupta (2008). In this paper, we generalize the univariate extended skew normal
distribution family to the matrix variate case. The moment
generating function, the distribution of the quadratic form and the
linear form, and the marginal and conditional distributions of this
family are studied.
© 2012 by Walter de Gruyter Berlin Boston
Articles in the same Issue
- Masthead
- Matrix variate extended skew normal distributions
- Run-length compression of quantized Gaussian stationary signals
- Random fixed point theorems for a finite family of asymptotically quasi-nonexpansive in the intermediate sense random operators
- The Elliptic Law. Thirty years later
Articles in the same Issue
- Masthead
- Matrix variate extended skew normal distributions
- Run-length compression of quantized Gaussian stationary signals
- Random fixed point theorems for a finite family of asymptotically quasi-nonexpansive in the intermediate sense random operators
- The Elliptic Law. Thirty years later
